Biblio
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2001. Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture. Proc. Int. Conf. Intelligent Robots and Sytems. :1570–1577.
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2005. Trends in Neurocomputing at ESANN 2004. Neurocomputing. 64:1–4.
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2013. Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. Robotik und Gesetzgebung. 2:51–71.
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2020. Kollaborative Roboter – universale Werkzeuge in der digitalisierten und vernetzten Arbeitswelt. G. W. Maier, G. Engels, E. Steffen (Hrg.): Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. :323-346.
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2002. Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.
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1999. Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.
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2019. Roboterlernen ohne Grenzen ? Lernende Roboter und ethische Fragen Christiane Woopen, Marc Jannes [Hrsg.] Roboter in der Gesellschaft. Technische Möglichkeiten und menschliche Verantwortung. :15-33.
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2005. Stability of backpropagtion-decorrelation efficient O(N) recurrent learning. Proc. European Symposium Artificial Neural Networks. :43–48.
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2008. Humans and Humanoids - Perspectives on Research in Cognition and Robotics. KI - Künstliche Intelligenz. 4:33–36.
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2019. Maschinelles Lernen und lernende Assistenzsysteme - Neue Tätigkeiten, Rollen und Anforderungen für Beschäftigte? Berufsbildung in Wissenschaft und Praxis – BWP. 3:14-18.
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2005. Memory in Backpropagation-Decorrelation O(N) Efficient Online Recurrent Learning. LNCS. 3697:649–654.
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2004. Neural Dynamics for Task-Oriented Grouping of Communicating Agents. Proc. European Symposium Artificial Neural Networks. :531–536.
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2007. Adaptive scene dependent filters for segmentation and online learning of visual objects. Neurocomputing. 70:1235–1246.
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1999. Recurrent Learning of Input-Output Stable Behaviour in Function Space: A Case Study with the Roessler Attractor. Proc. Int. Conf. Artificial Neural Networks. :761–766.
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2007. Online reservoir adaptation by intrinsic plasticity for backpropagation-decorrelation and echo state learning. Neural Networks. 20:353–364.
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2023. Mit KI zu mehr Teilhabe in der Arbeitswelt: Potenziale, Einsatzmöglichkeiten und Herausforderungen. Whitepaper aus der Plattform Lernende Systeme.
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2004. Backpropagation-Decorrelation: online recurrent learning with O(N) complexity. Proc. Int. Joint Conference Neural Networks. 1:843–848.
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2012. Intelligent Interfaces between Humans and Technology. 22:2.
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2000. Local input-output stability of recurrent networks with time-varying weights. Proc. European Symposium Artificial Neural Networks. :281–286.
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2013. Kinesthetic Teaching Using Assisted Gravity Compensation for Model-Free Trajectory Generation in Confined Spaces. Gearing Up and Accelerating Cross-Fertilization between Academic and Industrial Robotics Research in Europe. 94:107–127.
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2017. Robots in the digitalized workplace. The Wiley Blackwell Handbook of the Psychology of the Internet at Work. :403-422.
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2006. Online stability of backpropagation-decorrelation recurrent learning. Neurocomputing. 69:642–650.
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1998. Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Proc. Int. ICSC/IFAC Symposium on Neural Computation. :519–525.
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2004. Situated robot learning for multi-modal instruction and imitation of grasping. Robotics and Autonomous Systems. 47:129–141.
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2021. "Können Maschinen Ethisches Verhalten Lernen ?" Bericht zum 1. SYnENZ Zirkel der BWG Kommission für Synergie und Intelligenz (SYnENZ) Jahrbuch der Braunschweigischen Wissenschaftlichen Gesellschaft. :117-120.
